The National Airborne Field Experiment Data Sets
Bibliographic record
Abstract
The National Airborne Field Experiment’s(NAFE) were a series of intensive experiments recently conducted in different parts of Australia.These hydrologic-focused experiments have been designed to answer a range of questions which can only be resolved through carefully planned and executed field experiments in well instrumented basins together with intensive ground and airborne measurements of the appropriate type and spatial/temporal resolution.While the data collected have a specific focus on soil moisture, they are applicable to a wide range of hydrologic activities.The NAFE’05 experiment was undertaken in the Goulburn River catchment (New South Wales,Australia) during November 2005, with the objective of providing high resolution data for process level understanding of soil moisture retrieval, scaling and data assimilation. The NAFE’06 experiment was undertaken in the Murrumbidgee catchment (NSW, Australia)during November 2006, with the objective of providing data for SMOS (Soil Moisture and OceanSalinity; a dedicated soil moisture satellite to be launched in 2008) like soil moisture retrieval,downscaling and data assimilation.To meet these objectives, the Polarimetric L-band Multibeam Radiometer (PLMR), a thermal imager,full-wave transform lidar, tri-spectral scanner and digital camera were flown onboard a small aircraft,together with coincident ground data collection on soil moisture, rock coverage and temperature,surface roughness, land surface skin and soil temperature, vegetation dew amount and vegetation water content.Each campaign was 3 to 4 weeks in duration and encountered favourable meteorological conditions,meaning that data was collected across a range of soil moisture conditions. Moreover, data was collected across diverse landcover and landuse settings in two different climatic regimes. The data described in this paper are available on the WorldWide Web at www.nafe.unimelb.edu.au.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".